Cost-effectiveness analysis of the 70-gene signature compared with clinical assessment in breast cancer based on a randomised controlled trial.

BACKGROUND: The clinical utility of the 70-gene signature (MammaPrint®) to guide chemotherapy use in T1-3N0-1M0 breast cancer was demonstrated in the Microarray in Node-Negative and 1 to 3 Positive Lymph Node Disease May Avoid Chemotherapy (MINDACT) study. One thousand four ninety seven of 3356 (46.2%) enrolled patients with high clinical risk (in accordance with the modified Adjuvant! Online clinical-pathological assessment) had a low-risk 70-gene signature. Using patient-level data from the MINDACT trial, the cost-effectiveness of using the 70-gene signature to guide adjuvant chemotherapy selection for clinical high risk, estrogen receptor positive (ER+), human epidermal growth factor 2 negative (HER2-) patients was analysed. PATIENTS AND METHODS: A hybrid decision tree-Markov model simulated treatment strategies in accordance with the 70-gene signature with clinical assessment versus clinical assessment alone, over a 10-year time horizon. Primary outcomes were quality-adjusted life years (QALYs), country-specific costs and incremental cost-effectiveness ratios (ICERs) for six countries: Belgium, France, Germany, Netherlands, UK and the US. RESULTS: Treatment strategies guided by the 70-gene signature result in more QALYs compared with clinical assessment alone. Costs of the 70-gene signature strategy were lower in five of six countries. This led to dominance of the 70-gene signature in Belgium, France, Germany, Netherlands and the US and to a cost-effective situation in the UK (ICER £22,910/QALY). Annual national cost savings were €4.2M (Belgium), €24.7M (France), €45.1M (Germany), €12.7M (Netherlands) and $244M (US). UK budget increase was £8.4M. CONCLUSION: Using the 70-gene signature to safely guide chemotherapy de-escalation in clinical high risk patients with ER+/HER2- tumours is cost-effective compared with using clinical assessment alone. Long-term follow-up and outcomes from the MINDACT trial are necessary to address uncertainties in model inputs.

Assessment of Long-term Distant Recurrence-Free Survival Associated With Tamoxifen Therapy in Postmenopausal Patients With Luminal A or Luminal B Breast Cancer.

IMPORTANCE: Patients with estrogen receptor (ER)-positive breast cancer have a long-term risk for fatal disease. However, the tumor biological factors that influence the long-term risk and the benefit associated with endocrine therapy are not well understood. OBJECTIVE: To compare the long-term survival from tamoxifen therapy for patients with luminal A or luminal B tumor subtype. DESIGN, SETTING, AND PARTICIPANTS: Secondary analysis of patients from the Stockholm Tamoxifen (STO-3) trial conducted from 1976 to 1990, which randomized postmenopausal patients with lymph node-negative breast cancer to receive adjuvant tamoxifen or no endocrine therapy. Tumor tissue sections were assessed in 2014 using immunohistochemistry and Agilent microarrays. Only patients with luminal A or B subtype tumors were evaluated. Complete long-term follow-up data up to the end of the STO-3 trial on December 31, 2012, were obtained from the Swedish National registers. Data analysis for the secondary analysis was conducted in 2017 and 2018. INTERVENTIONS: Patients were randomized to receive at least 2 years of tamoxifen therapy or no endocrine therapy; patients without recurrence who reconsented were further randomized to 3 additional years of tamoxifen therapy or no endocrine therapy. MAIN OUTCOMES AND MEASURES: Distant recurrence-free interval (DRFI) by luminal A and luminal B subtype and trial arm was assessed by Kaplan-Meier analyses and time-dependent flexible parametric models to estimate time-varying hazard ratios (HRs) that were adjusted for patient and tumor characteristics. RESULTS: In the STO-3 treated trial arm, 183 patients had luminal A tumors and 64 patients had luminal B tumors. In the untreated arm, 153 patients had luminal A tumors and 62 had luminal B tumors. Age at diagnosis ranged from 45 to 73 years. A statistically significant difference in DRFI by trial arm was observed (log rank, P < .001 [luminal A subtype, n = 336], P = .04 [luminal B subtype, n = 126]): the 25-year DRFI for luminal A vs luminal B subtypes was 87% (95% CI, 82%-93%) vs 67% (95% CI, 56%-82%) for treated patients, and 70% (95% CI, 62%-79%) vs 54% (95% CI, 42%-70%) for untreated patients, respectively. Patients with luminal A tumors significantly benefited from tamoxifen therapy for 15 years after diagnosis (HR, 0.57; 95% CI, 0.35-0.94), and those with luminal B tumors benefited from tamoxifen therapy for 5 years (HR, 0.38; 95% CI, 0.24-0.59). CONCLUSIONS AND RELEVANCE: Patients with luminal A subtype tumors had a long-term risk of distant metastatic disease, which was reduced by tamoxifen treatment, whereas patients with luminal B tumors had an early risk of distant metastatic disease, and tamoxifen benefit attenuated over time.

Evaluation of National Comprehensive Cancer Network guideline-based Tool for Risk Assessment for breast and ovarian Cancer (N-TRAC): A patient-reported survey for genetic high-risk assessment for breast and ovarian cancers in women.

Identification of mutations that increase lifetime risk of breast and ovarian cancer is critical to improving women's health. Because these mutations are relatively rare in the general population, there is a need for efficient methods to identify appropriate women to undergo genetic testing. The objective of this study was to assess the feasibility, accuracy, and performance of the NCCN guideline-based Tool for Risk Assessment for breast and ovarian Cancer (N-TRAC)-a patient-facing assessment for those affected and unaffected by cancer. This study enrolled a prospective cohort of 100 affected and 100 unaffected women that used N-TRAC in a clinical setting. Recommendations for referral to genetic counseling based on N-TRAC and other standard risk assessment methods were compared.Seventy-seven of the 100 affected women and 35 of the 100 unaffected women were identified as high risk by N-TRAC. The average completion time was approximately 2 min for both groups. N-TRAC accuracy for family history was exceptional in both groups (kappa > 0.96). N-TRAC and other risk assessment methods do not always identify the same high risk population. N-TRAC is an accurate and feasible tool that can assist in identifying women at increased risk for hereditary breast and ovarian cancer and may lead to more informed decision-making.

New Horizons in Advocacy Engaged Physical Sciences and Oncology Research.

To address cancer as a multifaceted adaptive system, the increasing momentum for cross-disciplinary connectivity between cancer biologists, physical scientists, mathematicians, chemists, biomedical engineers, computer scientists, clinicians, and advocates is fueling the emergence of new scientific frontiers, principles, and opportunities within physical sciences and oncology. In parallel to highlighting the advances, challenges, and acceptance of advocates as credible contributors, we offer recommendations for addressing real world hurdles in advancing equitable partnerships among advocacy stakeholders.

The San Francisco Cancer Initiative: A Community Effort To Reduce The Population Burden Of Cancer.

The great potential for reducing the cancer burden and cancer disparities through prevention and early detection is unrealized at the population level. A new community-based coalition, the San Francisco Cancer Initiative (SF CAN), focuses on the city and county of San Francisco, where cancer is the leading cause of death. SF CAN is an integrated, cross-sector collaboration launched in November 2016. It brings together the San Francisco Department of Public Health; the University of California, San Francisco; major health systems; and community coalitions to exert collective impact. Its goals are to reduce the burden of five common cancers-breast, lung and other tobacco-related, prostate, colorectal, and liver-for which there are proven methods of prevention and detection, while reducing known disparities. We describe the infrastructure, coalition building, and early progress of this initiative, which may serve as a model for other municipalities.

Discordant assessment of tumor biomarkers by histopathological and molecular assays in the EORTC randomized controlled 10041/BIG 03-04 MINDACT trial breast cancer : Intratumoral heterogeneity and DCIS or normal tissue components are unlikely to be the cause of discordance.

Accurate identification of breast cancer patients most likely to benefit from adjuvant systemic therapies is crucial. Better understanding of differences between methods can lead to an improved ER, PgR, and HER-2 assessment. The purpose of this preplanned translational research is to investigate the correlation of central IHC/FISH assessments with microarray mRNA readouts of ER, PgR, and HER-2 status in the MINDACT trial and to determine if any discordance could be attributed to intratumoral heterogeneity or the DCIS and normal tissue components in the specimens. MINDACT is an international, prospective, randomized, phase III trial investigating the clinical utility of MammaPrint in selecting patients with early breast cancer for adjuvant chemotherapy (n = 6694 patients). Gene-expression data were obtained by TargetPrint; IHC and/or FISH were assessed centrally (n = 5788; 86 %). Macroscopic and microscopic evaluation of centrally submitted FFPE blocks identified 1427 cases for which the very same sample was submitted for gene-expression analysis. TargetPrint ER had a positive agreement of 98 %, and a negative agreement of 95 % with central pathology. Corresponding figures for PgR were 85 and 94 % and for HER-2 72 and 99 %. Agreement of mRNA versus central protein was not different when the same or a different portion of the tumor tissue was analyzed or when DCIS and/or normal tissue was included in the sample subjected to mRNA assays. This is the first large analysis to assess the discordance rate between protein and mRNA analysis of breast cancer markers, and to look into intratumoral heterogeneity, DCIS, or normal tissue components as a potential cause of discordance. The observed difference between mRNA and protein assessment for PgR and HER-2 needs further research; the present analysis does not support intratumoral heterogeneity or the DCIS and normal tissue components being likely causes of the discordance.

Cost-effectiveness of treatment strategies for BRAF-mutated metastatic melanoma.

PURPOSE: Genetically-targeted therapies are both promising and costly advances in the field of oncology. Several treatments for metastatic melanoma with a mutation in the BRAF gene have been approved. They extend life but are more expensive than the previous standard of care (dacarbazine). Vemurafenib, the first drug in this class, costs $13,000 per month ($207,000 for a patient with median survival). Patients failing vemurafenib are often given ipilimumab, an immunomodulator, at $150,000 per course. Assessment of cost-effectiveness is a valuable tool to help navigate the transition toward targeted cancer therapy. METHODS: We performed a cost-utility analysis to compare three strategies for patients with BRAF+ metastatic melanoma using a deterministic expected-value decision tree model to calculate the present value of lifetime costs and quality-adjusted life years (QALYs) for each strategy. We performed sensitivity analyses on all variables. RESULTS: In the base case, the incremental cost-effectiveness ratio (ICER) for vemurafenib compared with dacarbazine was $353,993 per QALY gained (0.42 QALYs added, $156,831 added). The ICER for vemurafenib followed by ipilimumab compared with vemurafenib alone was $158,139. In sensitivity analysis, treatment cost had the largest influence on results: the ICER for vemurafenib versus dacarbazine dropped to $100,000 per QALY gained with a treatment cost of $3600 per month. CONCLUSION: The cost per QALY gained for treatment of BRAF+ metastatic melanoma with vemurafenib alone or in combination exceeds widely-cited thresholds for cost-effectiveness. These strategies may become cost-effective with lower drug prices or confirmation of a durable response without continued treatment.

Turning the tide against cancer through sustained medical innovation: the pathway to progress.

An ever-expanding understanding of the molecular basis of the more than 200 unique diseases collectively called cancer, combined with efforts to apply these insights to clinical care, is forming the foundation of an era of personalized medicine that promises to improve cancer treatment. At the same time, these extraordinary opportunities are occurring in an environment of intense pressure to contain rising healthcare costs. This environment presents a challenge to oncology research and clinical care, because both are becoming progressively more complex and expensive, and because the current tools to measure the cost and value of advances in care (e.g., comparative effectiveness research, cost-effectiveness analysis, and health technology assessments) are not optimized for an ecosystem moving toward personalized, patient-centered care. Reconciling this tension will be essential to maintaining progress in a cost-constrained environment, especially because emerging innovations in science (e.g., increasing identification of molecular biomarkers) and in clinical process (implementation of a learning healthcare system) hold potential to dramatically improve patient care, and may ultimately help address the burden of rising costs. For example, the rapid pace of innovation taking place within oncology calls for increased capability to integrate clinical research and care to enable continuous learning, so that lessons learned from each patient treated can inform clinical decision making for the next patient. Recognizing the need to define the policies required for sustained innovation in cancer research and care in an era of cost containment, the stakeholder community must engage in an ongoing dialogue and identify areas for collaboration. This article reflects and seeks to amplify the ongoing robust discussion and diverse perspectives brought to this issue by multiple stakeholders within the cancer community, and to consider how to frame the research and regulatory policies necessary to sustain progress against cancer in an environment of constrained resources.

Gene expression profiling and breast cancer care: what are the potential benefits and policy implications?

PURPOSE: Gene expression profiling has been proposed as an alternative to clinical guidelines to identify high-risk patients for adjuvant chemotherapy. However, the outcomes associated with gene expression profiling are not clear, and guidelines for the appropriate use of genomic technologies have not been established. METHODS: We developed a decision analytic model to evaluate the incremental cost and quality-adjusted life years of gene expression profiling versus NIH clinical guidelines in a hypothetical cohort of premenopausal early stage breast cancer patients 44 years of age. We conducted empirical analyses and identified literature-based data to inform the model, and performed probabilistic sensitivity analyses to evaluate uncertainty in the results. We interpreted the implications of our findings for treatment guidelines and policies. RESULTS: Use of gene expression profiling resulted in an absolute 5% decrease in the proportion of cases of distant recurrence prevented, 0.21 fewer quality-adjusted life years, and a cost savings of USD 2882. The chosen test cutoff value to identify a tumor as poor prognosis and the cost of adjuvant chemotherapy were the most influential parameters in the analysis, but our findings did not change substantially in sensitivity analyses. Regardless of the test cutoff used to identify a poor prognosis tumor, the gene expression profiling assay studied in our analysis, at its current level of performance, did not attain the threshold sensitivity (95%) necessary to produce equal or greater quality-adjusted life years than NIH guidelines. CONCLUSION: Although the use of gene expression profiling in breast cancer care holds great promise, our analysis suggests additional refinement and validation are needed before use in clinical practice.